The American Dream or The American Delusion? The Private and External Benefits of Homeownership Grace W. Bucchianeri The Wharton School of Business Abstract: This paper uses a unique data set that links up well-being measures and housing characteristics to explore: (1) the relationship between homeownership and well-being; (2) time use pattern, family life, social connectedness and civic participation of homeowners; and (3) the implications of cross-sectional differences in neighborhood ownership rates, especially among subgroups of similar socio-economic status. The results show that after controlling for household income, housing quality, and health, homeowners are no happier than renters by any of the following definitions: life satisfaction, overall mood, overall feeling, general moment-to- moment emotions (i.e. affect) and affect at home but instead derive more pain from their house and home. Time use pattern analysis reveals that homeowners tend to spend less time on enjoyable activities. There is little evidence that homeowners are better citizens. Homeowners who live in ZIP code areas with higher rates of homeownership report more positive attitudes only if other owners are similar to them in socio-economic terms, lending some support to the idea of beneficial social interaction among owners.
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The American Dream or The American Delusion?
The Private and External Benefits of Homeownership
Grace W. Bucchianeri
The Wharton School of Business
Abstract: This paper uses a unique data set that links up well-being measures and housing characteristics to explore: (1) the relationship between homeownership and well-being; (2) time use pattern, family life, social connectedness and civic participation of homeowners; and (3) the implications of cross-sectional differences in neighborhood ownership rates, especially among subgroups of similar socio-economic status. The results show that after controlling for household income, housing quality, and health, homeowners are no happier than renters by any of the following definitions: life satisfaction, overall mood, overall feeling, general moment-to-moment emotions (i.e. affect) and affect at home but instead derive more pain from their house and home. Time use pattern analysis reveals that homeowners tend to spend less time on enjoyable activities. There is little evidence that homeowners are better citizens. Homeowners who live in ZIP code areas with higher rates of homeownership report more positive attitudes only if other owners are similar to them in socio-economic terms, lending some support to the idea of beneficial social interaction among owners.
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1. Introduction
Homeownership is central to the notion of the American Dream in the public
imagination. In a national survey, 65 percent of the respondents cited the “dream” as a major
reason to buy a home. (Fannie Mae 2003) It helps justify the mortgage interest tax deduction,
housing programs and policy platforms for politicians from either sides of the aisle. i This
romantic view of homeownership alludes to important private and external benefits of
homeownership, separate from the benefits of housing consumption on its own. Using a new data
set that provides information on housing consumption, well-being and time use patterns for about
six hundred women in Columbus, OH, this paper explores homeownership along three
dimensions: 1) the relationship between homeownership and well-being; 2) time use pattern,
family life, social connectedness and civic participation of homeowners; and 3) the implications
of cross-sectional differences in neighborhood homeownership rates, especially among
subgroups of similar socio-economic status.
The main contribution of this paper to the existing literature is apparent – the wide array
of both outcome variables and control variables enables a much more comprehensive and
credible comparison between owners and renters. My analysis explores subjective well-being
measures such as life satisfaction and emotions (affect) during family time to complement a
more traditional set of objective outcome measures such as BMI and time use patterns. The
explicit analysis of overall outcomes (such as happiness), specific outcome variables (such as joy
from children) and intermediate variables (such as time use patterns) helps fill in the gap in the
literature, which has so far focused on specific outcomes. (Dietz and Haurin 2003) I have also
limited my analysis to single-family home occupants, thus eliminating bias arising from
comparing different living arrangements and life styles in single-family homes and multi-family
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units. In Section 3, I examine in details the comparability of owners and renters, and the external
validity of the analysis given the non-standard aspects of the data set, including its gender and
geographical restrictions.
How much do we know about the benefits of homeownership? The literature on the
private benefits of homeownership is inconclusive despite the well-referenced but rarely
measured “pride of homeownership”. Rossi and Weber (1996) find that homeowners are happier
using the NSFH but not the GSS. In Rohe and Stegman (1994) and Rohe and Basolo (1997),
renters who became owners reported to be more satisfied than continuing renters. Galster (1987)
and other later studies, however, point out the ownership-happiness link might well be the result
of data limitation and the relationship between hard-to-measure neighborhood or personal
characteristics and homeownership. So far the evidence concerning the exact homeownership-
well-being mechanisms remain inconclusive. (Rohe et al. 2002) To shed light on this subject, I
first re-assess the owner-renter differences by controlling for a wide array of confounding
factors. I also directly investigate the potential channels homeownership might promote well-
being: self-esteem, health, joy and pain from related domains of life (e.g., neighborhood, family,
home), time use patterns and moment-to-moment emotions of homeowners in relation to their
leisure, family and social lives.
Previous work on the external benefits of homeownership focuses on social capital
generation and child outcomes.ii Attempts to measure the social capital related to homeownership
have produced different results. DiPasquale and Glaeser (1999) suggest that homeowners are
more active and involved citizens. Ellen et al. (2002) identify a causal link between two New
York City homeownership programs and price increases in surrounding neighborhoods in the
same ZIP code but provide no direct evidence on the mechanism. Green and White (1997),
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Boehm and Schlottmann (1999) and Haurin et al. (2002b & 2002c) identify better child
outcomes for homeowners, using different data and methodologies. A re-examination of the
issue by Barker and Miller (2009), however, finds that the beneficial effects of homeownership
previously measured are substantially reduced or eliminated by using a more comprehensive set
of controls. This paper builds on the existing literature and offers new evidence on time spent
with children and other family and social groups, and also emotions during those times. Other
than simply looking at the owner-renter differences in social connectedness and civic
participation, I explore the implications of a higher neighborhood homeownership rate,
especially among one’s own socio-economic group. So far the impacts of neighborhood
homeownership rates have been little studied, despite the numerous theories that support such
impacts. (Haurin et al. 2002a)
An interesting portrait of homeowners emerges from my analysis. While homeowners
report higher life satisfaction, more joy from both home and neighborhood and better moods on
an unadjusted basis, these promising differences become insignificant and much smaller in
magnitude once I control for a basic set of confounding factors: household income, housing
value and health status. Overall, I find little evidence that homeowners are happier by any of the
following definitions: life satisfaction, overall mood, overall feeling, general moment-to-moment
emotions (i.e., affect) and affect at home. The average homeowner, however, consistently derives
more pain (but no more joy) from their house and home. Although they are also more likely to be
12 pounds heavieriii
, report a lower health status and less joy from health, controlling for the less
favorable health status does not change the results. My findings are robust to controlling for
financial insecurity. Therefore, unadjusted differences in homeowners’ well-being might have
played an important role in establishing the popular beliefs about the American Dream.
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To help understand these surprising results, I investigate the homeowners’ time use
pattern, family and social lives. The average homeowner tends to spend less time on active
leisure or with friends, experience more negative affect during time spent with friends, derive
less joy from love and relationships and is also less likely to consider herself to enjoy being with
people. My results support neither the perception of gregarious homeowners nor that of
housework-burdened homeowners. In this paper, homeowners are also shown not to be
significantly different in terms of civic participation or social connectedness.
To reconcile this finding with the existing evidence, I explore the interaction of a
respondent’s homeownership status with the homeownership rates in her ZIP code overall and
among females in her ZIP code of similar socio-economic status (SES). The rationale behind this
is that social capital is likely created when homeowners interact, and that the externalities of
homeownership arise from an agglomeration and interaction of homeowners of similar SES
backgrounds. My findings are suggestive: The amount of reported pain from the neighborhood
decreases with various SES-specific ZIP code-level homeownership rates, though not with the
overall ZIP code-level homeownership rate. This is in line with the conclusion of Cummings et
al. (2002) that homeownership programs have no significant benefit spillovers when there is a
lack of interaction between homeowners and the greater community.
Clearly, the empirical setting is not ideal for testing causality links. In addition to the
wide array of control variables available in this data, there exist other potential confounding
factors related to the homeownership status, such as personality. However, given that those who
derive more joy from homeownership are more likely to become homeowners and thus the
unobserved confounding factors likely cause an upward bias in well-being outcomes, it is still
useful to interpret my results as upper bounds of the benefits of homeownership. Moreover, the
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survey took place during a boom market (May 2005), which might also relate to a relatively
sunny view on housing by homeowners. Another important feature of the data sample is worth
keeping in mind: because Franklin County, OH, is very similar to the national average, it is more
useful to think about the implications of the results for the median household rather than
subgroups of the population. These results are not easily generalized to an assessment of low-
income or minority housing policies. Section 3 expands on the applicability of results in this
paper.
The rest of the paper is organized as follows: Sections 2 and 3 describe and examine the
data; Sections 4 to 7 present and discuss the empirical evidence; Section 8 concludes.
2. Data
This paper makes use of three separate data sets: the Day Reconstruction Method (DRM)
Survey, the property tax records and the 2000 United States Census.
All well-being, demographic and time use variables are derived from the DRM Survey.iv
It is a survey of 809 women in Columbus, OH, in 2005. Reliability of the data is analyzed by
Krueger and Schkade (2008). It has been shown that the DRM method yields similar results to
the gold standard, the experience sampling technique. (Kahneman et al. 2004a) First, information on moment-to-moment emotions (affect) is collected. Respondents
were asked to divide the previous day (“reference day”) into episodes that lasted for between 20
minutes and 2 hours. They were to start a new episode whenever there was a significant change
in what they were doing, whom they were interacting with or their emotions. Respondents
described each episode by indicating: (1) when the episode began and ended; (2) what they were
doing, by checking as many activities that applied from a list of 16 possible activities (plus other)
that included working, watching television, socializing, etc.; (3) where they were; (4) whom they
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were interacting with, if anyone (co-workers, friends, spouse, children, etc.). Respondents next
reported the intensity of 10 affective dimensions during each episode (Impatient,
Rossi, P.H., Weber E., 1996. The Social Benefits of Homeownership: Empirical Evidence From
National Surveys, Housing Policy Debate 7(1), 1-35.
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Endnotes
i For example, see The American Dream Downpayment Act 2003. Fannie Mae claims to be in the American Dream
business, helping Americans “realize their American Dream of owning a home”. ii Obviously, child outcomes also yield private benefits so related results are discussed along with other private
benefits of homeownership. iii
Calculation is based on the differences on BMI and the average height of American women. Please see Section 5
for more details. iv See Kahneman et al. (2004) for a discussion and evaluation of the Day Reconstruction Method. The questionnaires
and related documentation are available upon request. v These emotions were chosen to represent points along the Russell (1980) circumplex. See Krueger (2007).
vi Note that Columns 7 and 8 use respondents’ own estimates of their overall mood in a typical day, while Columns 9
and 10 represent duration-weighted affect during episodes throughout the reference day. vii
In results not shown, four proxies for stress – levels of agreement with: “often worries for nothing”, “a bit
depressed”, “tense and uncomfortable”; amount of pain derived from financial (in)security – are studied and they
show no relationship to homeownership status. viii
Less than 20 percent of the women in the sample regularly engage in volunteer or charity work, so the power of
the related analysis is limited.
Variable Obs Mean [s.d.] Obs Mean [s.d.] Obs Mean [s.d.]
Survey Variables
Proportion of awake time spent at home 492 0.547 71 0.525 563 0.004
[0.237] [0.254] (0.031)
Proportion of episodes occurred during weekend 492 0.335 71 0.437 563 -0.090
[0.473] [0.499] (0.057)
Total no. of episodes at home 492 7.744 71 6.746 563 0.866
[4.221] [4.544] (0.549)
Total no. of episodes outside home 492 6.175 71 5.986 563 0.398
***=Significant at 1%; **=Significant at 5%; *=Significant at 10%
Dependent Variables
Table 2 - Are Homeowners Happier?
Control Set 1 is a set of basic controls including Income, Housing price and Health. Control Set 2 contains additional demographic variables including an age quadratic, education,
cohabitation and living with children indicators. Control Set 3 includes a full control set with a financial security indicator and ZIP Code-level income and education measures.
Note: Subjective dependent variables are re-scaled using the sample standard deviations. Therefore coefficients in related regressions can be interpreted as changes in terms of
standard deviations associated with a change in homeownership status.
***=Significant at 1%; **=Significant at 5%; *=Significant at 10%
Table 5 - Homeownership and Time Use Patterns by Activities
Dependent Variables
Control Set 1 is a set of basic controls including Income and housing price. Control Set 2 contains additional demographic variables including an age
quadratic, education, cohabitation and living with children indicators. Control Set 3 includes a full control set with a financial security indicator and
***=Significant at 1%; **=Significant at 5%; *=Significant at 10%
Control Set 1 is a set of basic controls including Income and housing price. Control Set 2 contains additional demographic variables including an age quadratic, education, cohabitation and living with children indicators. Control Set 3 includes a full control set with a financial security indicator and ZIP Code-level income and
education measures.
Note: Net affect variables are re-scaled using the sample standard deviations. Therefore coefficients in related regressions can be interpreted as changes in terms of standard deviations associated with a change in homeownership status.
Table 6 - Homeownership and Time Use Patterns by Social Interaction
Full sample Living with spouse/significant other
% time spent with spouse/ significant
other
Net affect during time spent with
spouse/significant other
Living with children Full sample
Joy from children Joy from family Joy from friends
***=Significant at 1%; **=Significant at 5%; *=Significant at 10%
Table 7 - Homeownership and Reported Joy from Domains of LifeDependent variables
Control Set 1 is a set of basic controls including Income and housing price. Control Set 2 contains additional demographic variables including an age quadratic, education, cohabitation and living with
children indicators. Control Set 3 includes a full control set with a financial security indicator and ZIP Code-level income and education measures.
Note: Subjective dependent variables are re-scaled using the sample standard deviations. Therefore coefficients in related regressions can be interpreted as changes in terms of standard deviations associated
with a change in homeownership status.
Regularly
do volunteer
or charity
work
Joy from
activity in the
community
Pain from
activity in the
community
Pain from the
politics of the
country
(1) (2) (3) (4)
(1) Unadjusted 0.058 0.131 -0.090 0.016
(0.052) (0.127) (0.122) (0.124)
Observations 563 561 561 561
Adj. R-squared 0.000 0.000 -0.001 -0.002
(2) Control Set 1 0.055 0.001 0.089 0.050
(0.061) (0.146) (0.141) (0.145)
Observations 550 548 548 548
Adj. R-squared -0.001 0.034 0.034 -0.001
(3) Control Set 2 -0.015 -0.108 -0.077 -0.078
(0.066) (0.158) (0.153) (0.158)
Observations 549 547 547 547
Adj. R-squared 0.010 0.045 0.048 0.003
(4) Control Set 3 -0.026 -0.097 -0.070 -0.043
(0.067) (0.159) (0.154) (0.158)
Observations 548 546 546 546
Adj. R-squared 0.013 0.053 0.053 0.021
Standard errors shown in parentheses
***=Significant at 1%; **=Significant at 5%; *=Significant at 10%
Dependent Variables
Table 8 - Homeownership and Civic Activities
Control Set 1 is a set of basic controls including Income and housing price.
Control Set 2 contains additional demographic variables including an age
quadratic, education, cohabitation and living with children indicators. Control
Set 3 includes a full control set with a financial security indicator and ZIP Code-
level income and education measures.
Note: Subjective dependent variables are re-scaled using the sample standard
deviations. Therefore coefficients in related regressions can be interpreted as
changes in terms of standard deviations associated with a change in
***=Significant at 1%; **=Significant at 5%; *=Significant at 10%
Control Set 1 is a set of basic controls including Income and housing price. Control Set 2 contains additional demographic variables including an age quadratic, education, cohabitation and living with children indicators. Control Set
3 includes a full control set with a financial security indicator and ZIP Code-level income and education measures.
Note: Subjective dependent variables are re-scaled using the sample standard deviations. Therefore coefficients in related regressions can be interpreted as changes in terms of standard deviations associated with a change in
homeownership status.
Table 9 - Neighborhood Homeownership Rate by SES
Pain from house and homeJoy from neighborhood Joy from house and home Pain from neighborhood
Dependent Variables
(1) (2) (3) (4) (5) (6)
Joy from neighborhood: 'some' -0.019 -- 0.006 -- -- --
(0.034) (0.033)
Joy from neighborhood: 'a lot' -0.031 -- 0.005 -- -- --
(0.033) (0.041)
Pain from neighborhood: 'some' -- 0.060** 0.059** -- -- --
(0.032) (0.031)
Pain from neighborhood: 'a lot' -- 0.252*** 0.261*** -- -- --
(0.129) (0.142)
Joy from house and home: 'some' -- -- -- -0.079* -- -0.052
(0.042) (0.046)
Joy from house and home: 'a lot' -- -- -- -0.096** -- -0.054
(0.050) (0.051)
Pain from house and home: 'some' -- -- -- -- 0.005 0.004
(0.028) (0.027)
Pain from house and home: 'a lot' -- -- -- -- 0.131** 0.099*
(0.075) (0.073)
Observations 422 422 421 422 422 421
R-squared 0.003 0.043 0.043 0.017 0.024 0.029
Dependent Variable: =1 If Respondent Moved During the 12 Months Post-Survey
Appendix Table A1 - Residential Mobility and Well-being Measures
Dependent Variable: Log Sales Price
Log total finished living area 0.571***
(0.076)
Log building age -0.031**
(0.015)
No. of bedrooms -0.008
(0.029)
No. of family rooms -0.041
(0.033)
No. of dining rooms 0.060*
(0.035)
No. of half baths 0.059
(0.036)
No. of full baths 0.027
(0.036)
Attic dummy 0.038
(0.053)
Air-conditioning dummy 0.042
(0.050)
Fireplace dummy 0.037
(0.033)
Remodelled dummy 0.019
(0.038)
Neighborhood desirability: fair 0.206
(0.410)
Neighborhood desirability: average 0.296
(0.414)
Neighborhood desirability: good 0.345
(0.415)
Neighborhood desirability: very good 0.497
(0.416)
One Garage dummy 0.033
(0.056)
2+ Garage dummy 0.147***
(0.054)
Types of exterior wall (base group=wood/ Al)
Stucco 0.092
(0.065)
Stone -0.033
(0.061)
Masonry 0.072**
(0.031)
Building conditions (base group=average)
Fair 0.312***
(0.106)
Good 0.374***
(0.108)
Very good 0.450***
(0.148)
Zipcode fixed effects Yes
Year fixed effects Yes
Observations 416
R-squared 0.855
* significant at 10%; ** significant at 5%; *** significant at 1%
Appendix Table A2: Hedonic Price Model
Regression is performed using all available home sales of single-family homes. Log sales
values are predicted for all single-family homes in the sample with the year of transaction
adjusted to 2005.
(1) (2) (3) (4) (5) (6)
Sleep quality during the previous month -0.943*** -0.835*** -0.822*** -1.026*** -0.670** -0.586**
(0.091) (0.110) (0.108) (0.240) (0.286) (0.285)
Avg hours of sleep during the previous month -- -0.125* 0.044 -- -0.343** -0.164
(0.072) (0.078) (0.159) (0.184)
Hours of sleep the previous night -- -- -0.244*** -- -- -0.271*